RESEARCH ARTICLE

Ecosystem Carbon Storage in Alpine Grassland on the Qinghai Plateau Shuli Liu1,2, Fawei Zhang1, Yangong Du1, Xiaowei Guo1, Li Lin1, Yikang Li1, Qian Li1, Guangmin Cao1* 1 Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai, China, 2 University of Chinese Academy of Sciences, Beijing, China * [email protected]; [email protected]

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OPEN ACCESS Citation: Liu S, Zhang F, Du Y, Guo X, Lin L, Li Y, et al. (2016) Ecosystem Carbon Storage in Alpine Grassland on the Qinghai Plateau. PLoS ONE 11(8): e0160420. doi:10.1371/journal.pone.0160420 Editor: Shilong Piao, Peking University, CHINA Received: February 21, 2016 Accepted: July 19, 2016 Published: August 5, 2016 Copyright: © 2016 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract The alpine grassland ecosystem can sequester a large quantity of carbon, yet its significance remains controversial owing to large uncertainties in the relative contributions of climate factors and grazing intensity. In this study we surveyed 115 sites to measure ecosystem carbon storage (both biomass and soil) in alpine grassland over the Qinghai Plateau during the peak growing season in 2011 and 2012. Our results revealed three key findings. (1) Total biomass carbon density ranged from 0.04 for alpine steppe to 2.80 kg C m-2 for alpine meadow. Median soil organic carbon (SOC) density was estimated to be 16.43 kg C m-2 in alpine grassland. Total ecosystem carbon density varied across sites and grassland types, from 1.95 to 28.56 kg C m-2. (2) Based on the median estimate, the total carbon storage of alpine grassland on the Qinghai Plateau was 5.14 Pg, of which 94% (4.85 Pg) was soil organic carbon. (3) Overall, we found that ecosystem carbon density was affected by both climate and grazing, but to different extents. Temperature and precipitation interaction significantly affected AGB carbon density in winter pasture, BGB carbon density in alpine meadow, and SOC density in alpine steppe. On the other hand, grazing intensity affected AGB carbon density in summer pasture, SOC density in alpine meadow and ecosystem carbon density in alpine grassland. Our results indicate that grazing intensity was the primary contributing factor controlling carbon storage at the sites tested and should be the primary consideration when accurately estimating the carbon storage in alpine grassland.

Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: This work was supported by National Natural Science Foundation of China (41030105) and “Strategic Priority Research Program — Climate Change: Carbon Budget, Related Issues” of the Chinese Academy of Sciences (XDA05050404). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist.

Introduction China’s terrestrial ecosystems (both vegetation and soils) have been estimated to have sequestered 20.8–26.8% of the carbon released in industrial CO2 emissions during 1981–2000 [1]. It is reported that the grasslands of China (331×106 ha) cover only 6–8% of the total world grassland area but contain 9–16% of the world’s total carbon [2]. To date, a large number of estimates of the forest ecosystem carbon stocks in China have been reported [3,4], but a comprehensive assessment of carbon storage in China’s grasslands is still lacking [5]. Estimating the level of carbon stored in living vegetation and soil organic matter in grassland

PLOS ONE | DOI:10.1371/journal.pone.0160420 August 5, 2016

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ecosystems has been limited by the lack of direct measurements and the large spatial heterogeneity of grassland ecosystems [6–8]. Accurately estimating carbon storage in vegetation and soil is not only essential for understanding current levels of carbon pools, but also for mapping how these terrestrial ecosystem carbon pools change over time, which is critical for evaluating the global carbon budget, the main predictor of climate change [9,10]. Alpine grasslands on the Tibetan Plateau constitute 34.3% of the total grassland in China [11] and comprise 56.4% of the total grasslands biomass carbon in China [6]. This indicates that carbon storage in alpine grasslands likely plays a significant role in global carbon cycles [12]. Surprisingly, the importance of carbon storage, in particular biomass carbon, in alpine grassland has not been well recognized due to the variations in topography and access [13]. Biomass data are needed to estimate levels of carbon storage, and are best provided by the collection of field data [4,14]. Currently there are very limited field observations of biomass in the alpine grassland of the Qinghai Plateau, so to accurately estimate ecosystem (biomass and soil) carbon storage, ground-based observational data are required. Both biomass and soil carbon stock in terrestrial ecosystems may respond to climate change and disturbance caused by human activities [15,16]. Alpine ecosystems have been shown to have a greater and more rapid response to warming scenarios [17], and are also influenced by human activities such as livestock grazing [18]. To accurately estimate ecosystem carbon budget, the effects of climate factors and grazing intensity must be taken into account. The goals of this study are: (1) to estimate total ecosystem (both biomass and soil) carbon storage in alpine grassland, and (2) to quantitatively define the influences of climate and grazing on the carbon density in alpine grassland. This study will help to clarify the current levels of carbon storage in alpine grassland, and will enhance our understanding of the roles that climate change and grazing intensity play on carbon budget.

Materials and Methods Study area The study sites were located on the Qinghai-Tibetan Plateau in Qinghai Province. The area covered 36.37×104 km2, extending from 92.17 to 101.75°E in longitude and from 30.29 to 38.60°N in latitude [19]. The region experiences a typical plateau climate, with a cool, short summer and a cold, long and dry winter, and thus the growing season is short compared to other areas at similar latitudes [17]. The average elevation was 4000 m, the mean annual temperature ranged from -5°C to 12°C [20], and the annual precipitation was 500 mm—800 mm, of which over 80% fell during the summer season [21]. Alpine grassland was the main vegetation type in the area. Based on China’s vegetation classification system, we divided the alpine grasslands in this region into two types: alpine steppe and alpine meadow [22]. The distribution of grassland types was obtained from China’s vegetation atlas at a scale of 1:1,000,000 (Chinese Academy of Sciences, 2001). This classification, along with the locations of the 115 sampling sites, is shown in Fig 1. The area of the alpine steppe and alpine meadow was extracted from the map.

Sampling method We aimed to measure the biomass of above- and below-ground carbon as well as soil carbon at 115 sites during 2011 and 2012. At each site, no specific permits were demanded for collecting samples and the field studies did not involve endangered or protected species. The sites included mostly winter pasture (grazing from November to April) and some summer pasture (grazing from May to October). At each site (10 m × 100 m), five 0.25 m2 (0.5 m × 0.5 m) and five 1 m2 (1 m × 1 m) quadrats were sampled in the alpine meadow and alpine steppe,

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Fig 1. Spatial distribution of sampling sites in alpine grasslands on the Qinghai Plateau. The vegetation map of the plateau was obtained from China’s vegetation atlas at a scale of 1: 1,000,000 (Chinese Academy of Sciences, 2001). Also shown are locations of the 115 sites surveyed during 2011–2012. doi:10.1371/journal.pone.0160420.g001

respectively. The geographical location of each site was determined by a Global Positioning Satellite (GPS) device. At each site the altitude, longitude, latitude, grassland types, total vegetation cover, dominant species and land use types were recorded. Peak above-ground biomass (AGB) was measured by the clipping method in both winter and summer pasture during July and September. Quadrats were located at 20 m intervals along the 100 m × 10 m sites and all plants (both alive and dead) in the five small quadrats (0.5 m × 0.5 m for alpine meadow and 1 m × 1 m for alpine steppe) were harvested to ground level. Below-ground biomass (BGB) was also measured during the growing season, following AGB collection in the quadrats. To assess BGB, a soil core (6 cm diameter) was used to collect samples and was divided into seven depth increments (0–5, 5–10, 10–20, 20–30, 30–50, 50–70 and 70–100 cm). Five soil samples from each depth interval on the same quadrats were lumped together and then cleaned under running water to remove soil particles. Roots were passed through a 2-mm sieve to remove fine roots (< 2 mm). Live and dead roots could not be distinguished; hence, the BGB values included both live and dead roots [23]. The biomass samples (both AGB and BGB) were oven dried at 65°C to a constant mass and then weighed to the

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nearest 0.1 g. The carbon concentration of biomass (both live and dead biomass) was measured by the dry combustion method using an elemental analyzer (2400 II CHNS/O, Perkin-Elmer, USA). The biomass carbon density of each site was calculated by multiplying the carbon concentration and the respective mass of each AGB and BGB component within the site [24]. Soil samples were collected using the same method as that for BGB samples and were divided into seven depth increments (0–5, 5–10, 10–20, 20–30, 30–50, 50–70 and 70–100 cm). In the laboratory, the soil samples were air-dried and then sieved to 0.25 mm. Soil carbon concentration was also measured by elemental analyzer (2400 II CHNS/O, Perkin-Elmer, USA). We calculated SOC density in the top 1 m of each sample using the method of stratified cumulative sum (Eq 1). SOCD ¼

n X

SOCi  Pi  Di  ð1  Ci Þ=100

ð1Þ

i¼1

Where SOCD is the SOC density (kg C m-2) of the profile, SOCi is the SOC concentration (g kg-1), Ρi is the bulk density (g cm-3), Di is the soil thickness (cm), and Ci is the volume percent of gravel (particle sizes > 2 mm) in layer i, respectively. The mean annual temperature (MAT) and mean annual precipitation (MAP) were extracted from the climate database of Qinghai Province for the period 1971–2010 [25]. Livestock data for each county were obtained from the prairie station of Qinghai Province during 2011–2012 and calculated according to standard conversions in which one yak is equivalent to 4.5 sheep units and one horse is equivalent to 6 sheep units (Agricultural industry standard of the people's Republic of China, 2002).

Statistical analysis For all data analysis, preliminary normality testing was carried out to ensure the normality of the data. Linear mixed-effects model (LME) analysis was performed to test the possible dependency of ecosystem carbon density on environmental factors. Then ordinary least squares (OLS) regression analysis was conducted to evaluate the relationships between ecosystem carbon density and the climate or grazing factors. We have excluded the effects of the other explanatory variables while assessing the effect of one explanatory variable. All statistical analyses were performed in SPSS 16.0 (SPSS Inc. Chicago, IL, USA). In all cases, a P value

Ecosystem Carbon Storage in Alpine Grassland on the Qinghai Plateau.

The alpine grassland ecosystem can sequester a large quantity of carbon, yet its significance remains controversial owing to large uncertainties in th...
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